Adaptive document ranking method based on user behavior

• US 20020103798A1
• Filed: 02/01/2001
• Published: 08/01/2002
• Est. Priority Date: 02/01/2001
• Status: Abandoned Application

• Current Assignee: Verity Incorporated (Healthstream Incorporated)
• Original Assignee: Verity Incorporated (Healthstream Incorporated)
• Inventors: Abrol, Mani S., Johnson, Brett M.
• Application Number:
  US09/775,715
• Publication Number:
  US 20020103798A1
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/3326 using relevance feedback from the user, e.g. relevance feedback on documents, documents sets, document terms or passages
• CPC Class Codes: G06F 16/3347 using vector based model
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

A user behavior based document ranking system and method permit prior user behavior associated with a document to affect the future ranking of that document. Thus, the ranking system and method in accordance with the invention incorporates user behavior into the document ranking process.

Claims

1. A system for user behavior based ranking of a document, comprising:

means for determining a feature vector associated with a document, the feature vector comprising weights for certain terms that appear in the document; and

means for modifying the feature vector for the document based on user actions during a search session so that the document is more highly ranked in response to the user actions.

2. The system of claim 1 further comprising means for collecting user actions in response to a list of documents produced in response to a query wherein the user actions include selecting a document from the list of documents.

3. The system of claim 2 further comprises means for adjusting the weights of the terms in the feature vector that match terms in a query that produced the list of documents so that the ranking of the document is higher in response to the adjustment of the weights.

4. A method for user behavior based ranking of a document, comprising:

determining a feature vector associated with a document, the feature vector comprising weights for one or more terms that appear in the document; and

modifying the feature vector for the document based on user actions during a query of the document so that the document is more highly ranked in response to the user actions.

5. The method of claim 4 further comprising means for collecting user actions in response to a list of documents produced in response to a query wherein the user actions include selecting a document from the list of documents.

6. The method of claim 5, wherein the modifying means further comprises means for adjusting the frequency values of the terms in the feature vector that match terms in a query that produced the list of documents so that the ranking of the document is higher in response to the adjustment of the frequency values.

7. A system for user behavior based searching of a document based on a query having one or more query terms, comprising:

means for determining a feature vector associated with a document, the feature vector comprising weights for certain terms that appear in the document;

means for modifying the feature vector for the document based on user actions during a query of the document so that the document is more highly ranked in response to the user actions; and

means for returning the same document to another user with the same query at a higher ranking due to the modified feature vector.

8. The system of claim 7 further comprising means for collecting user actions in response to a list of documents produced in response to a query wherein the user actions include selecting a document from the list of documents.

9. The system of claim 8, wherein the modifying means further comprises means for adjusting the frequency values of the terms in the feature vector that match terms in a query that produced the list of documents so that the ranking of the document is higher in response to the adjustment of the frequency values.

10. A method for user behavior based searching of a document based on a query having one or more query terms, comprising:

determining a feature vector associated with a document, the feature vector comprising frequency values for one or more terms that appear in the document;

modifying the feature vector for the document based on user actions during a query of the document so that the document is more highly ranked in response to the user actions; and

returning the same document to another user with the same query at a higher ranking due to the modified feature vector.

11. The method of claim 10 further comprising means for collecting user actions in response to a list of documents produced in response to a query wherein the user actions include selecting a document from the list of documents.

12. The method of claim 11, wherein the modifying means further comprises means for adjusting the frequency values of the terms in the feature vector that match terms in a query that produced the list of documents so that the ranking of the document is higher in response to the adjustment of the frequency values.